عزت الله عباسیان

The certainty about retirement income is dependent on the longevity and the selected investment policy by individuals during their working years. Attention to longevity and investment risks is of high significance in making enough income for retirees. In this research, the impact of the objective formulation selection on investment decisions has been investigated. Two functions including terminal wealth objective formulation and retirement income objective formulation are applied to investigate these decisions. Based on the investment alternatives, 5 asset classes including Equity, Certificate of deposit (cash), real estate investment trust (REIT), gold coin, and foreign exchange have been selected for investment. According to the complexity of modeling in the aforementioned functions, the Metaheuristic Genetic algorithm has been used. The results are indicative of the importance of objective formulation selection. The retirement income objective function has the nature of more wealth accumulation and more control over economic and market turbulences through higher cooperation in investment and as a result, it has been recommended as the optimal function.

Purpose: Education is one of the important factors of economic and social development and the education industry is one of the largest and most tangible industries in the world. Therefore, the aim of this study was to providing a customer value maturity model based on the dynamic capabilities of educational institutions. Methodology: This study in terms of purpose was applied and in terms of implementation method was qualitative. In this study number of 15 people after checking the inclusion criteria such as work experience of at least 10 years and at least bachelor's education with using the purposive sampling method were selected from among the experts of non-governmental educational institutions of the senior school in Tehran city. The tool of the current research was a semi-structured interview with selected experts, which its validity was confirmed by the triangulation method and its reliability was calculated by the method of the coefficient of agreement between two coding 0.88. Data were analyzed by content analysis method. Findings: The results of the present study indicated that for the customer value maturity model based on the dynamic capabilities of educational institutions were identified number of 268 open codes in 5 core codes or levels, respectively including the analysis the value proposition of customer, definition and design the value proposition of customer, management and expansion the value proposition of customer, implementation and execution the value proposition of customer and evaluation and optimization the value proposition of customer. Therefore, the educational programs in the customer value maturity model based on the dynamic capabilities of educational institutions were drawn at five levels based on the level of maturity and value. Conclusion: According to the identified codes and levels for the customer value maturity model based on the dynamic capabilities of educational institutions can be taken an effective step in the direction of customer value maturity.